# -*- coding: utf-8 -*- """ GPT-SoVITS 持久化工具类 包含：模型配置、参考音频、推理参数 的持久化读写与管理 抽离自主文件，减少主文件臃肿，方便后续维护 """ import json import yaml import hashlib import os import shutil import random from pathlib import Path # ===================== 全局配置（统一管理所有持久化文件路径） ===================== # 模型持久化配置文件 LAST_SELECTED_MODELS_JSON = Path("./last_selected_models.json") # 参考预设最后选中配置文件 LAST_SELECTED_PRESET_JSON = Path("./last_selected_preset.json") # 参考音频持久化目录 REF_AUDIO_DIR = Path("GPT_SoVITS/ref_audios") # 参考预设配置文件 REF_PRESETS_YAML = Path("GPT_SoVITS/configs/ref_audios_presets.yaml") # 推理参数配置文件 INFER_SETTINGS_JSON = Path("GPT_SoVITS/configs/infer_settings.json") # 参考音频配置常量 MAX_FILENAME_LENGTH = 40 INVALID_FILE_CHARS = set(r'\/:*?"<>|') # 默认推理参数 DEFAULT_INFER_SETTINGS = { "batch_size": 20, "sample_steps": 32, "fragment_interval": 0.2, "speed_factor": 1.0, "top_k": 5, "top_p": 1.0, "temperature": 1.0, "repetition_penalty": 1.35, "how_to_cut": "凑四句一切", "super_sampling": False, "parallel_infer": True, "split_bucket": True, "seed": -1, "keep_random": True } # ===================== 通用工具函数（抽离重复逻辑） ===================== def sanitize_filename(name): """清理文件名中的非法字符，替换为下划线""" if not name: return "unnamed_preset" return ''.join(c if c not in INVALID_FILE_CHARS else '_' for c in name) def get_audio_md5(file_path, chunk_size=4096): """计算音频文件的MD5值（取前8位），用于区分不同音频内容""" if not os.path.exists(file_path): return "invalid_file" try: md5 = hashlib.md5() with open(file_path, 'rb') as f: while chunk := f.read(chunk_size): md5.update(chunk) return md5.hexdigest()[:8] except Exception as e: print(f"计算音频MD5失败：{e}") return f"err_{random.randint(10000000, 99999999)}" def ensure_dir_exists(dir_path): """确保目录存在，不存在则创建""" if dir_path and not dir_path.exists(): dir_path.mkdir(exist_ok=True, parents=True) # ===================== 1. 模型配置持久化（last_selected_models.json） ===================== def init_last_selected_models(gpt_default, sovits_default, current_version): """初始化模型配置文件，写入默认模型路径""" ensure_dir_exists(LAST_SELECTED_MODELS_JSON.parent) init_data = { "gpt_model_path": gpt_default, "sovits_model_path": sovits_default, "version": current_version } with open(LAST_SELECTED_MODELS_JSON, "w", encoding="utf-8") as f: json.dump(init_data, f, ensure_ascii=False, indent=4) print(f"首次生成模型配置文件：{LAST_SELECTED_MODELS_JSON}") return init_data def read_last_selected_models(): """读取模型配置文件中的路径""" if not LAST_SELECTED_MODELS_JSON.exists(): return None try: with open(LAST_SELECTED_MODELS_JSON, "r", encoding="utf-8") as f: data = json.load(f) # 校验必要字段 required_fields = ["gpt_model_path", "sovits_model_path", "version"] for field in required_fields: if field not in data: return None return data except Exception as e: print(f"读取模型配置失败：{e}") return None def write_last_selected_models(gpt_path_new, sovits_path_new, current_version): """写入新的模型路径到配置文件""" ensure_dir_exists(LAST_SELECTED_MODELS_JSON.parent) try: data = read_last_selected_models() or {} data["gpt_model_path"] = gpt_path_new data["sovits_model_path"] = sovits_path_new data["version"] = current_version with open(LAST_SELECTED_MODELS_JSON, "w", encoding="utf-8") as f: json.dump(data, f, ensure_ascii=False, indent=4) except Exception as e: print(f"写入模型配置失败：{e}") # ===================== 2. 参考音频预设持久化（last_selected_preset.json + ref_audios_presets.yaml） ===================== # 2.1 最后选中预设的读写清 def read_last_selected_preset(): """读取最后一次选中的预设名称""" if not LAST_SELECTED_PRESET_JSON.exists(): return None try: with open(LAST_SELECTED_PRESET_JSON, "r", encoding="utf-8") as f: data = json.load(f) return data.get("last_selected_preset") except Exception as e: print(f"读取最后选中预设失败：{e}") return None def write_last_selected_preset(preset_name): """写入最后一次选中的预设名称""" ensure_dir_exists(LAST_SELECTED_PRESET_JSON.parent) try: data = {"last_selected_preset": preset_name.strip()} with open(LAST_SELECTED_PRESET_JSON, "w", encoding="utf-8") as f: json.dump(data, f, ensure_ascii=False, indent=4) print(f"已记录最后选中的预设：{preset_name.strip()}") except Exception as e: print(f"写入最后选中预设失败：{e}") def clear_last_selected_preset(): """清空最后选中的预设记录""" if not LAST_SELECTED_PRESET_JSON.exists(): return try: with open(LAST_SELECTED_PRESET_JSON, "w", encoding="utf-8") as f: json.dump({"last_selected_preset": ""}, f, ensure_ascii=False, indent=4) except Exception as e: print(f"清空最后选中预设失败：{e}") # 2.2 参考预设配置的加载/保存/删除 def load_ref_presets(): """加载多组参考预设配置""" ensure_dir_exists(REF_PRESETS_YAML.parent) # 新增：配置文件不存在时，自动创建空文件 if not REF_PRESETS_YAML.exists(): with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f: yaml.dump([], f, indent=4, allow_unicode=True) print(f"暂未检测到参考预设配置文件，已自动创建空文件：{REF_PRESETS_YAML}") return [] try: with open(REF_PRESETS_YAML, "r", encoding="utf-8") as f: presets = yaml.load(f, Loader=yaml.FullLoader) or [] # 兼容旧格式转换 if isinstance(presets, dict): presets = [{"name": "旧配置转换", "ref_audio_path": presets.get("ref_audio_path"), "prompt_text": presets.get("prompt_text", ""), "prompt_language": presets.get("prompt_language", "中文")}] # 补充缺失字段 + 校验音频路径 default_template = {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"} for preset in presets: for key, value in default_template.items(): preset.setdefault(key, value) # 校验音频路径有效性 audio_path = preset["ref_audio_path"] if audio_path and not os.path.exists(str(audio_path)): preset["ref_audio_path"] = None # 清理冗余音频 clean_unreferenced_audios(presets) print(f"参考预设加载成功，共 {len(presets)} 组") return presets except Exception as e: print(f"参考预设加载失败：{e}") return [] def get_preset_by_name(preset_name, presets=None): """根据配置名称查询对应的配置详情""" # 核心修复：先判断 preset_name 是否为 None，避免 AttributeError if preset_name is None: return {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"} if not presets: presets = load_ref_presets() # 现在再调用 strip()，确保 preset_name 不是 None preset_name_str = preset_name.strip() for preset in presets: if preset["name"].strip() == preset_name_str: return preset # 无匹配预设时，返回空的合法预设字典 return {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"} def save_ref_preset_core(preset_name, ref_audio_path, prompt_text, prompt_language, confirm_override=False): """保存/覆盖参考预设核心逻辑（返回：提示信息、是否成功、预设列表）""" ensure_dir_exists(REF_AUDIO_DIR) presets = load_ref_presets() preset_name = preset_name.strip() # 前置校验 if not ref_audio_path or not os.path.exists(str(ref_audio_path)): return "保存失败！请先上传有效的主参考音频文件。", False, [p["name"] for p in presets] if not preset_name: return "保存失败！配置名称不能为空。", False, [p["name"] for p in presets] # 音频持久化处理 persistent_audio_path = get_persistent_audio_path(ref_audio_path, preset_name) if not persistent_audio_path: return "保存失败！音频文件持久化存储失败。", False, [p["name"] for p in presets] # 同名检测 preset_index = -1 for idx, p in enumerate(presets): if p["name"].strip() == preset_name: preset_index = idx break if preset_index >= 0 and not confirm_override: return f"配置「{preset_name}」已存在，如需替换请确认覆盖！", False, [p["name"] for p in presets] # 构造新配置 new_preset = { "name": preset_name, "ref_audio_path": persistent_audio_path, "prompt_text": prompt_text, "prompt_language": prompt_language } # 更新配置列表 is_new_preset = preset_index < 0 if preset_index >= 0: presets[preset_index] = new_preset tip = "同名配置已覆盖！" else: presets.append(new_preset) tip = "新配置已新增！" # 写入配置文件 try: with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f: yaml.dump(presets, f, indent=4, allow_unicode=True) # 新增预设自动记录为最后选中 if is_new_preset: write_last_selected_preset(preset_name) preset_names = [p["name"] for p in presets] return f"配置保存成功！{tip}", True, preset_names except Exception as e: return f"保存失败：{str(e)}", False, [p["name"] for p in presets] def delete_ref_preset_core(preset_name): """删除参考预设核心逻辑（返回：提示信息、预设列表、默认选中预设）""" presets = load_ref_presets() preset_name = preset_name.strip() if not presets: return "暂无配置可删除！", [], None # 获取待删除音频路径 target_audio_path = None for p in presets: if p["name"].strip() == preset_name: target_audio_path = p.get("ref_audio_path") break # 过滤删除 presets = [p for p in presets if p["name"].strip() != preset_name] # 写入配置文件 try: with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f: yaml.dump(presets, f, indent=4, allow_unicode=True) # 删除对应音频 if target_audio_path and os.path.exists(target_audio_path): os.unlink(target_audio_path) print(f"同步删除配置对应音频：{target_audio_path}") # 清空最后选中记录（若删除的是最后选中的预设） last_selected = read_last_selected_preset() if last_selected and last_selected == preset_name: clear_last_selected_preset() preset_names = [p["name"] for p in presets] new_selected = preset_names[0] if preset_names else None tip = "配置删除成功！已同步清理对应音频文件" if preset_names else "配置删除成功！已同步清理对应音频文件，当前无剩余配置" return tip, preset_names, new_selected except Exception as e: return f"删除失败：{str(e)}", [p["name"] for p in presets], preset_name # 2.3 参考音频文件管理 def get_persistent_audio_path(src_audio_path, preset_name): """获取音频持久化路径，清理同配置名旧音频""" if not src_audio_path or not os.path.exists(src_audio_path): return None # 清理文件名 safe_preset_name = sanitize_filename(preset_name) safe_preset_name = safe_preset_name[:MAX_FILENAME_LENGTH] # 提取后缀 src_suffix = Path(src_audio_path).suffix.lower() if not src_suffix or src_suffix not in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]: src_suffix = ".wav" # 计算MD5 audio_md5 = get_audio_md5(src_audio_path) dst_filename = f"{safe_preset_name}_{audio_md5}{src_suffix}" dst_path = REF_AUDIO_DIR / dst_filename # 清理同配置名旧音频 for old_audio in REF_AUDIO_DIR.glob(f"{safe_preset_name}_*"): if old_audio.suffix.lower() in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]: try: old_audio.unlink() except Exception as e: print(f"清理旧音频失败：{e}") # 复制新音频 try: shutil.copy2(src_audio_path, dst_path) return str(dst_path) except Exception as e: print(f"音频持久化复制失败：{e}") return None def clean_unreferenced_audios(presets): """清理未被任何预设引用的冗余音频""" if not REF_AUDIO_DIR.exists(): return # 收集已引用音频 referenced = set() for preset in presets: audio_path = preset.get("ref_audio_path") if audio_path and os.path.exists(audio_path): referenced.add(Path(audio_path).absolute()) # 删除未引用音频 deleted_count = 0 for audio_file in REF_AUDIO_DIR.glob("*"): if audio_file.is_file() and audio_file.suffix.lower() in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]: if audio_file.absolute() not in referenced: try: audio_file.unlink() deleted_count += 1 except Exception as e: print(f"清理冗余音频失败：{e}") if deleted_count > 0: print(f"清理冗余未引用音频 {deleted_count} 个") # ===================== 3. 推理参数持久化（infer_settings.json） ===================== def load_infer_settings(): """加载推理参数配置""" ensure_dir_exists(INFER_SETTINGS_JSON.parent) if not INFER_SETTINGS_JSON.exists(): return DEFAULT_INFER_SETTINGS try: with open(INFER_SETTINGS_JSON, "r", encoding="utf-8") as f: saved = json.load(f) return {**DEFAULT_INFER_SETTINGS, **saved} except Exception as e: print(f"加载推理参数失败，使用默认值：{e}") return DEFAULT_INFER_SETTINGS def save_infer_settings_core(settings): """保存推理参数核心逻辑（返回：提示信息）""" ensure_dir_exists(INFER_SETTINGS_JSON.parent) try: with open(INFER_SETTINGS_JSON, "w", encoding="utf-8") as f: json.dump(settings, f, indent=4, ensure_ascii=False) # 精简日志输出 print(f"✅ 推理配置保存成功：{INFER_SETTINGS_JSON.absolute()}") return "推理设置保存成功！已覆盖原有配置文件。" except Exception as e: print(f"❌ 推理配置保存失败：{e}") return f"推理设置保存失败：{str(e)}" def restore_default_infer_settings_core(): """恢复推理参数默认值核心逻辑（返回：默认参数列表）""" ensure_dir_exists(INFER_SETTINGS_JSON.parent) try: with open(INFER_SETTINGS_JSON, "w", encoding="utf-8") as f: json.dump(DEFAULT_INFER_SETTINGS, f, indent=4, ensure_ascii=False) print(f"✅ 推理配置已恢复默认值：{INFER_SETTINGS_JSON.absolute()}") except Exception as e: print(f"❌ 推理配置恢复默认失败：{e}") # 返回默认参数（按顺序对应UI组件） return [ DEFAULT_INFER_SETTINGS["batch_size"], DEFAULT_INFER_SETTINGS["sample_steps"], DEFAULT_INFER_SETTINGS["fragment_interval"], DEFAULT_INFER_SETTINGS["speed_factor"], DEFAULT_INFER_SETTINGS["top_k"], DEFAULT_INFER_SETTINGS["top_p"], DEFAULT_INFER_SETTINGS["temperature"], DEFAULT_INFER_SETTINGS["repetition_penalty"], DEFAULT_INFER_SETTINGS["how_to_cut"], DEFAULT_INFER_SETTINGS["super_sampling"], DEFAULT_INFER_SETTINGS["parallel_infer"], DEFAULT_INFER_SETTINGS["split_bucket"], DEFAULT_INFER_SETTINGS["seed"], DEFAULT_INFER_SETTINGS["keep_random"] ]